The present invention relates generally to synthetic array radar imaging systems, and more particularly, to an improved scaleable range migration algorithm for use in high-resolution, large-area synthetic array radar imaging systems.
Traditional synthetic array radar (SAR) image formation processors for high-resolution imaging have employed a classic polar format algorithm (PFA). The image must be sufficiently small so that performance issues (range walk, defocusing and geometric distortion) are within tolerable limits, which is known as the depth-of-field (or depth-of-focus). Large-area imaging is handled by breaking up the scene into smaller subimages, processing each subimage with its own center point, and piecing the resulting subimages together as well as possible.
The polar format algorithm does not provide for a truly scalable implementation. Real-time processing is achieved by designing subimage sizes that are matched to a given number of processing nodes and creating specialized, efficient software. The number of nodes dictated the design of the software. Each processing platform requires a tailored implementation, and this led to non-portable software.
More particularly, disadvantages of the polar format algorithm approach are: (1) discontinuities across the subimage boundaries, and (2) lack of true processing scalability. Discontinuities are undesirable for image exploitation algorithms such as interferometric SAR and coherent change detection. Lack of true scalability makes it difficult to assign the subimages to the processing nodes so that load balancing is achieved. Optimal balancing usually requires an integral number of subimages per processing node.
Adding more processing nodes, with the intent of speeding up the processing to real time, may entail the redesigning of subimage sizes so that optimal load balancing is once again achieved. This is a very difficult problem to solve if one desires a processing approach that employs parameter-driven software. The same software must run on any number of nodes by simply changing a few parameters (which is the definition of scalable processing).
The basic range migration algorithm is described in a book entitled Spotlight SAR by Carrara et al, is representative of a class of SAR imaging algorithms that are called wavenumber domain techniques. In theory, the range migration algorithm performs large-area imaging without having to break up the scene into smaller subimages, and it provides for scalable and portable processing. However, the range migration algorithm requires a special computationally-intensive preprocessing step known as range deskew. This preprocessing synchronizes (in time) the radar returns from multiple point targets, and it also eliminates the residual video phase (RVP) term in the input phase history. Synchronizing the returns is not desirable for the imaging of very large swath widths.
Accordingly, it is an objective of the present invention to provide for an improved scalable range migration algorithm for use in high-resolution, large-area synthetic array radar imaging systems. It is a further objective of the present invention to provide for an improved scalable range migration algorithm that overcomes the limitations of the classic range migration algorithm.